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Machines 2018, 6(4), 55; https://doi.org/10.3390/machines6040055

Joint Optimization of Preventive Maintenance, Spare Parts Inventory and Transportation Options for Systems of Geographically Distributed Assets

1
Program of Operations Research and Industrial Engineering, University of Texas at Austin, 204 E. Dean Keeton St, Austin, TX 78712, USA
2
Department of Mechanical Engineering, University of Texas at Austin, 204 E. Dean Keeton St, Austin, TX 78712, USA
*
Author to whom correspondence should be addressed.
Received: 1 September 2018 / Revised: 7 October 2018 / Accepted: 18 October 2018 / Published: 1 November 2018
(This article belongs to the Special Issue Artificial Intelligence for Cyber-Enabled Industrial Systems)
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Abstract

Maintenance scheduling for geographically dispersed assets intricately and closely depends on the availability of maintenance resources. The need to have the right spare parts at the right place and at the right time inevitably calls for joint optimization of maintenance schedules and logistics of maintenance resources. The joint decision-making problem becomes particularly challenging if one considers multiple options for preventive maintenance operations and multiple delivery methods for the necessary spare parts. In this paper, we propose an integrated decision-making policy that jointly considers scheduling of preventive maintenance for geographically dispersed multi-part assets, managing inventories for spare parts being stocked in maintenance facilities, and choosing the proper delivery options for the spare part inventory flows. A discrete-event, simulation-based meta-heuristic was used to optimize the expected operating costs, which reward the availability of assets and penalizes the consumption of maintenance/logistic resources. The benefits of joint decision-making and the incorporation of multiple options for maintenance and logistic operations into the decision-making framework are illustrated through a series of simulations. Additionally, sensitivity studies were conducted through a design-of-experiment (DOE)-based analysis of simulation results. In summary, considerations of concurrent optimization of maintenance schedules and spare part logistic operations in an environment in which multiple maintenance and transpiration options are available are a major contribution of this paper. This large optimization problem was solved through a novel simulation-based meta-heuristic optimization, and the benefits of such a joint optimization are studied via a unique and novel DOE-based sensitivity analysis. View Full-Text
Keywords: integrated decision-making; preventive maintenance; spare parts logistics; transportation selection integrated decision-making; preventive maintenance; spare parts logistics; transportation selection
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Wang, K.; Djurdjanovic, D. Joint Optimization of Preventive Maintenance, Spare Parts Inventory and Transportation Options for Systems of Geographically Distributed Assets. Machines 2018, 6, 55.

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